20,251 research outputs found
Material modelling and springback analysis for multi-stage rotary draw bending of thin-walled tube using homogeneous anisotropic hardening model
The aim of this paper is to compare several hardening models and to show their relevance for the prediction of springback and deformation of an asymmetric aluminium alloy tube in multi-stage rotary draw bending process. A three-dimensional finite-element model of the process is developed using the ABAQUS code. For material modelling, the newly developed homogeneous anisotropic hardening model is adopted to capture the Bauschinger effect and transient hardening behaviour of the aluminium alloy tube subjected to non-proportional loading. The material parameters of the hardening model are obtained from uniaxial tension and forward-reverse shear test results of tube specimens. This work shows that this approach reproduces the transient Bauschinger behaviour of the material reasonably well. However, a curve-crossing phenomenon observed for this material cannot be captured by the homogeneous anisotropic hardening model. For comparison purpose, the isotropic and combined isotropic-kinematic hardening models are also adopted for the analysis of the same problem. The predictions of springback and cross-section deformation based on these models are discussed. (C) 2014 The Authors. Published by Elsevier Ltd.open1134Nsciescopu
Photometric identification of blue horizontal branch stars
We investigate the performance of some common machine learning techniques in
identifying BHB stars from photometric data. To train the machine learning
algorithms, we use previously published spectroscopic identifications of BHB
stars from SDSS data. We investigate the performance of three different
techniques, namely k nearest neighbour classification, kernel density
estimation and a support vector machine (SVM). We discuss the performance of
the methods in terms of both completeness and contamination. We discuss the
prospect of trading off these values, achieving lower contamination at the
expense of lower completeness, by adjusting probability thresholds for the
classification. We also discuss the role of prior probabilities in the
classification performance, and we assess via simulations the reliability of
the dataset used for training. Overall it seems that no-prior gives the best
completeness, but adopting a prior lowers the contamination. We find that the
SVM generally delivers the lowest contamination for a given level of
completeness, and so is our method of choice. Finally, we classify a large
sample of SDSS DR7 photometry using the SVM trained on the spectroscopic
sample. We identify 27,074 probable BHB stars out of a sample of 294,652 stars.
We derive photometric parallaxes and demonstrate that our results are
reasonable by comparing to known distances for a selection of globular
clusters. We attach our classifications, including probabilities, as an
electronic table, so that they can be used either directly as a BHB star
catalogue, or as priors to a spectroscopic or other classification method. We
also provide our final models so that they can be directly applied to new data.Comment: To appear in A&A. 19 pages, 22 figures. Tables 7, A3 and A4 available
electronically onlin
Scheme for sharing classical information via tripartite entangled states
We investigate schemes for quantum secret sharing and quantum dense coding
via tripartite entangled states. We present a scheme for sharing classical
information via entanglement swapping using two tripartite entangled GHZ
states. In order to throw light upon the security affairs of the quantum dense
coding protocol, we also suggest a secure quantum dense coding scheme via W
state in analogy with the theory of sharing information among involved users.Comment: 4 pages, no figure. A complete rewrritten vession, accepted for
publication in Chinese Physic
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